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In China, traditional food is a significant element of culture that affects human behaviors. The point of interest (POI) of traditional food restaurants' location and their volatile organic compounds (VOCs) emissions affect the urban ecology. Rather than examine potential urban development patch (PUDP) based on land use data, the perspective of this paper is to examine the PUDP, air quality, and food culture in urban ecology in Chengdu, China. Methods: First, the research identifies three types of PUDP models (open PUDP, landscape PUDP, and conflict PUDP) with the weighted overlay of land use data, then uses machine learning to examine the relationship between PUDP, POI of traditional food restaurant, and VOCs. Results: The study generates three types of PUDP which are open PUDP, landscape PUDP, and conflict PUDP. VOCs and POI of traditional restaurant have a strong correlation, and both have a significant negative correlation with open PUDP. However, the landscape PUDP and conflict PUDP do not show an obvious relationship with food POI and VOCs. Conclusion: The results indicate that the future urban ecology should consider restaurant location, VOCs from restaurants, and their relationship to urban land use data as they have a strong relationship. [ABSTRACT FROM AUTHOR]

PM2.5 particles with an aerodynamic diameter of less than 2.5 μm are receiving increasing attention in China. Understanding how complex factors affect PM2.5 particles is crucial for the prevention of air pollution. This study investigated the influence of meteorological factors and land use on the dynamics of PM2.5 concentrations in four urban agglomerations of China at different scales from 2010 to 2020, using the Durbin spatial domain model (SDM) at five different grid scales. The results showed that the average annual PM2.5 concentration in four core urban agglomerations in China generally had a downward trend, and the meteorological factors and land use types were closely related to the PM2.5 concentration. The impact of temperature on PM2.5 changed significantly with an increase in grid scale, while other factors did not lead to obvious changes. The direct and spillover effects of different factors on PM2.5 in inland and coastal urban agglomerations were not entirely consistent. The influence of wind speed on coastal urban clusters (the Pearl River urban agglomeration (PRD) and Yangtze River urban agglomeration (YRD)) was not significant among the meteorological factors, but it had a significant impact on inland urban clusters (the Beijing–Tianjin–Hebei urban agglomeration (BTH) and Chengdu–Chongqing urban agglomeration (CC)). The direct effect of land use type factors showed an obvious U-shaped change with an increase in the research scale in the YRD, and the direct effect of land use type factors was almost twice as large as the spillover effect. Among land use type factors, human factors (impermeable surfaces) were found to have a greater impact in inland urban agglomerations, while natural factors (forests) had a greater impact in coastal urban agglomerations. Therefore, targeted policies to alleviate PM2.5 should be formulated in inland and coastal urban agglomerations, combined with local climate measures such as artificial precipitation, and urban land planning should be carried out under the consideration of known impacts. [ABSTRACT FROM AUTHOR]

Black carbon (BC), an important component of atmospheric aerosol, plays a significant role in regional climate, hydrological cycle, variation of monsoon rainfall, and human health. The 40-year detailed atmospheric BC over China from 1981 to 2020 is systematically investigated through the MERRA-2 reanalysis dataset. MERRA-2 BC generally showed a good correlation (R = 0.68) compared with 673 monthly samples from ground-based observation at 35 stations around China. The overall annual average of MERRA-2 BC concentration over China is 1.15 μg/m3, with a fast growth rate during 1981–2007 and a relatively slow decrease after that. The winter season has the highest mean concentration of BC, followed by autumn and spring, whereas summer shows relatively weaker values. The order of annual average BC concentrations during 1981–2020 is Beijing-Tianjin-Hebei region (BTH, 4.02 μg/m3) > Sichuan Basin (SB, 3.94 μg/m3) > Yangtze River Delta (YRD, 2.68 μg/m3) > Pearl River Delta (PRD, 1.47 μg/m3). The monthly mean BC concentrations over the BTH, YRD, PRD and SB are estimated to be smallest 3.18 μg/m3 in May, 1.94 μg/m3 in August, 0.82 μg/m3 in July, 3.04 μg/m3 in June, respectively, whilst largest consistently in December with 5.09 μg/m3, 3.83 μg/m3, 2.12 μg/m3, and 5.41 μg/m3, respectively. Our study indicates the primary potential source areas for BC are concentrated in the research city and its surroundings. Beijing and Chengdu are more BC-polluted areas than Shanghai and Guangzhou. Long-distance, regional transfer from south BTH contributes importantly to BC pollution in Beijing under the influence of prevailing southerly winds. The geographical location of Chengdu causes the transport and accumulation of BC inside the SB. [ABSTRACT FROM AUTHOR]

In recent years, haze pollution is frequent, which seriously affects daily life and production process. The main factors to measure the degree of smoke pollution are the concentrations of PM2.5 and PM10. Therefore, it is of great significance to study the prediction of PM2.5/PM10 concentration. Since PM2.5 and PM10 concentration data are time series, their time characteristics should be considered in their prediction. However, the traditional neural network is limited by its own structure and has some weakness in processing time related data. Recurrent neural network is a kind of network specially used for sequence data modeling, that is, the current output of the sequence is correlated with the historical output. In this paper, a haze prediction model is established based on a deep recurrent neural network. We obtained air pollution data in Chengdu from the China Air Quality Online Monitoring and Analysis Platform, and conducted experiments based on these data. The results show that the new method can predict smog more effectively and accurately, and can be used for social and economic purposes. [ABSTRACT FROM AUTHOR]

Meteorological conditions significantly influence air pollution. The Chengdu plain, with few external pollution sources and homogeneous meteorological conditions, is a natural lab to study the effects of meteorological elements on the diffusion and dissipation of pollutants. Large-scale and long-duration haze events occurred all over China during the Spring Festival in 2014. This study tries to detect the characteristics and the formation mechanisms of this haze event in the Chengdu area using air quality and the meteorological monitoring of this event. The results showed that, when considering the concentration changes of the primary pollutant, this haze event could be divided into three stages: Stage 1, the concentration of all pollutions increased; Stage 2, the concentration of gaseous pollutants decreased, while that of particulate matter increased; Stage 3, the concentration of all pollutants decreased. Adverse atmospheric circulation, unfavorable meteorological conditions (lower air temperature and wind speed, higher air pressure and relative humidity), a frequently occurring inversion layer (with a strong intensity and lower bottom), and the low height of the mixing layer resulted in this haze. This study suggests that not only surface meteorological factors, but also the boundary layer structure, played an important role in the vertical diffusion of the pollutants. [ABSTRACT FROM AUTHOR]

Ground-level ozone (O3) pollution has become a serious environmental issue in major urban agglomerations in China. To investigate the spatiotemporal patterns and regional transports of O3 in Beijing–Tianjin–Hebei (BTH-UA), the Yangtze River Delta (YRD-UA), the Triangle of Central China (TC-UA), Chengdu–Chongqing (CY-UA), and the Pearl River Delta urban agglomeration (PRD-UA), multiple transdisciplinary methods were employed to analyze the O3-concentration data that were collected from national air quality monitoring networks operated by the China National Environmental Monitoring Center (CNEMC). It was found that although ozone concentrations have decreased in recent years, ozone pollution is still a serious issue in China. O3 exhibited different spatiotemporal patterns in the five urban agglomerations. In terms of monthly variations, O3 had a unimodal structure in BTH-UA but a bimodal structure in the other urban agglomerations. The maximum O3 concentration was in autumn in PRD-UA, but in summer in the other urban agglomerations. In spatial distribution, the main distribution of O3 concentration was aligned in northeast–southwest direction for BTH-UA and CY-UA, but in northwest–southeast direction for YRD-UA, TC-UA, and PRD-UA. O3 concentrations exhibited positive spatial autocorrelations in BTH-UA, YRD-UA, and TC-UA, but negative spatial autocorrelations in CY-UA and PRD-UA. Variations in O3 concentration were more affected by weather fluctuations in coastal cities while the variations were more affected by seasonal changes in inland cities. O3 transport in the center cities of the five urban agglomerations was examined by backward trajectory and potential source analyses. Local areas mainly contributed to the O3 concentrations in the five cities, but regional transport also played a significant role. Our findings suggest joint efforts across cities and regions will be necessary to reduce O3 pollution in major urban agglomerations in China. [ABSTRACT FROM AUTHOR]

Air pollution is becoming increasingly serious along with social and economic development in the southwest of China. The distribution characteristics of particle matter (PM) were studied in Chengdu from 2016 to 2017, and the changes of PM bearing water-soluble ions and heavy metals and the distribution of secondary ions were analyzed during the haze episode. The results showed that at different pollution levels, heavy metals were more likely to be enriched in fine particles and may be used as a tracer of primary pollution sources. The water-soluble ions in PM2.5 were mainly Sulfate-Nitrate-Ammonium (SNA) accounting for 43.02%, 24.23%, 23.50%, respectively. SO42−, NO3−, NH4+ in PM10 accounted for 34.56%, 27.43%, 19.18%, respectively. It was mainly SO42− in PM at Clean levels (PM2.5 = 0~75 μg/m3, PM10 = 0~150 μg/m3), and mainly NH4+ and NO3− at Light-Medium levels (PM2.5 = 75~150 μg/m3, PM10 = 150~350 μg/m3). At Heavy levels (PM2.5 = 150~250 μg/m3, PM10 = 350~420 μg/m3), it is mainly SO42− in PM2.5, and mainly NH4+ and NO3− in PM10. The contribution of mobile sources to the formation of haze in the study area was significant. SNA had significant contributions to the PM during the haze episode, and more attention should be paid to them in order to improve air quality. [ABSTRACT FROM AUTHOR]

Ground-level ozone (O3), which is mainly from the photochemical reactions of NOx and volatile organic compounds (VOCs), has become a crucial pollutant obstructing air quality improvement in China. Understanding the composition, temporal variability and source apportionment of VOCs is necessary for determining effective control measures to minimize VOCs and their related photochemical pollution. To provide a comprehensive analysis of VOC sources and their contributions to ozone formation in the city of Chengdu—a megacity with the highest rates of industrial and economic development in southwest China—we conducted a one-month monitoring project at three urban sites (Shuangliu, Xindu, Junpingjie; SL, XD and JPJ, respectively) along the main north–south meteorological transport channel before and during the implemented control measures. Alkanes were the dominant group at each site, contributing to around 50% of the observed total VOCs, followed by oxygen-containing VOCs (OVOCs), aromatics, halohydrocarbons and alkenes. During the control period, the mixing ratios of most measured VOC species decreased, and O3 concentrations were down by at least 20%. VOC species experiencing the most effect from control were aromatics and OVOCs, which had higher O3 formation reactivity. This indicated that the control policies had significant influence on reductions of reactive VOC species. We also identified VOC sources at SL and XD using positive matrix factorization (PMF) and assessed their contributions to photochemical O3 formation by calculating the O3 formation potential (OFP) based on mass concentrations and maximum incremental reactivity of related VOCs. Five dominant VOC sources were identified, with the highest contributions from vehicular exhaust and fuel evaporation before control, followed by solvent utilization, biogenic background and secondary formation, and industrial emissions. Contribution from vehicular exhaust was reduced the most at SL, while at XD, secondary formation VOCs decreased significantly. VOCs from vehicular and industrial emissions and solvent utilization were found to be the dominant precursors for OFPs, particularly the species of xylenes, toluene and propene. Our results therefore suggest that priority should be given to the alleviation of photochemical pollutants for effective control of O3 formation in Chengdu. The findings from this work have important implications for formulating effective emission control policies in Chengdu. [ABSTRACT FROM AUTHOR]